creating app.py filr

app.py

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+import gradio as gr
+from diffusers import StableDiffusionPipeline
+import torch
+
+# Load the model (Make sure to set up the correct model path)
+pipe = StableDiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16)
+pipe = pipe.to("cuda")
+
+# Define the function to process the uploaded image
+def generate_headshot(image):
+    # Process the uploaded image and generate a professional headshot
+    generated_image = pipe(image).images[0]
+    return generated_image
+
+# Create the Gradio interface
+iface = gr.Interface(fn=generate_headshot, inputs=gr.Image(), outputs=gr.Image(), title="Professional Headshot Generator")
+
+# Launch the interface
+iface.launch()